The subject matter disclosed herein relates to leak detection and, in particular, to systems and methods for detection and display of effluent using optical detection systems, e.g., thermal imaging systems.
Many industries seek efficient means to perform in-situ detection of leaks and other component failures that allow effluent to discharge, e.g., from pipes, tanks, etc. By detecting leaks early, these industries can avoid the discharge of large amounts of materials, many of which may be carcinogenic, toxic, flammable, and explosive. Early detection can reduce the cost of necessary clean-up and decontamination, as well as limit repair costs and improve profits by stemming the flow of material that is lost, e.g., by leakage from a pipeline. In fact, regulations in some industries often require constant monitoring of equipment to control and reduce the incidence of leakage.
One type of in-situ detection systems have sensing devices that detect volatile organic compounds (VOCs) and other gases. Although accurate to generate gas concentration readings, these sniffer systems are labor-intensive and require the sensing devices to be in close proximity to the components under observation. Another type of detection system utilizes optical detection. These systems deploy devices including lasers and cameras sensitive to various wavelengths of electromagnetic radiation (e.g., infra-red). Thermal imaging systems, for example, are optical detection systems that can generate a video image. Processing of this video image can graphically display temperature distributions, which can prove useful for some types of leak detection.
Unfortunately, thermal imaging does not provide a robust solution for the broad range of fluids (e.g., gas and liquids) that may require in-situ detection technology. For example, detection of specific temperatures on the temperature distributions as an indicator of leakage or spills is likely unreliable because the absolute or radiation temperatures of spilled fluids is often unknown. Moreover, conventional controls (e.g., gain and level controls) and other color algorithms found on thermal imaging systems do not provide adequate visualization of leaks and spills because of the low signal levels and broad dynamic temperature range found in scenes under observation. Thermal imaging is particularly difficult for materials that exhibit particularly low thermal signatures, e.g., gasses.
To address some of these issues, leak detection systems may utilize various image processing techniques. Difference imaging, for example, is one technique that compares images to identify certain thermal changes that might indicate a leak or spill. The images may include a background (or pre-spill) thermal image and a current (or spill) thermal image. The comparison removes the dynamic temperature range of the scene. Difference imaging and related techniques do not, however, comport with continually changing ambient conditions. Nor do these techniques deal well with changes in the sensitivity of thermal imaging equipment. Rather, changes in the scene and/or equipment can give rise to spurious signals that are indistinguishable from signals that indicate that a spill or leak is underway. Other image processing techniques compare a pre-stored reference image, which shows a view of a known, non-leaking part or component, to a current image of the component under observation. In this case, problems can arise because the current image must show the component under observation in exactly the same orientation and view as the component that is found in the reference image. Other leak detection systems, e.g. pyroelectrics and similar AC coupled detectors, inherently apply difference imaging. These systems, however, require an external chopper wheel in order to produce a continuous stream of video that includes both the dynamic scene temperature changes and the unchanging background.